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Measures of the Geographic Concentration of Industries: Improving Distance-Based Methods

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  • Eric Marcon

    (ECOFOG - Ecologie des forêts de Guyane - CIRAD : UMR93 - CNRS : UMR2728 - INRA : UMR0745 - Université des Antilles et de Guyane - AgroParisTech)

  • Florence Puech

    (LET - Laboratoire d'économie des transports - CNRS : UMR5593 - Université Lumière - Lyon II - Ecole Nationale des Travaux Publics de l'Etat)

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    Abstract

    This study introduces two new measures of spatial concentration. The proposed M functions constitute an extension to Ripley's functions (Ripley, 1976, 1977). They allow the evaluation of the relative geographic concentration and co-location of industries in a non-homogeneous spatial framework. Some rigorous comparisons with similar recently developed tools prove the relevance of the M functions in the field of spatial economics.

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    Bibliographic Info

    Paper provided by HAL in its series Working Papers with number halshs-00372617.

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    Date of creation: 01 Apr 2009
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    Handle: RePEc:hal:wpaper:halshs-00372617

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    Related research

    Keywords: Geographic concentration ; Distance-based methods ; Ripley's K function ; M function;

    References

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    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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    1. Gilles Duranton & Henry G. Overman, 2006. "Exploring the detailed location patterns of UK manufacturing industries using microgeographic data," LSE Research Online Documents on Economics 19794, London School of Economics and Political Science, LSE Library.
    2. Haaland, J.I. & Kind, H.J. & knarvik, K.H.M. & Torstensson, J., 1998. "What Determines the Economic Geography of Europe?," Papers 19/98, Norwegian School of Economics and Business Administration-.
    3. Eric Marcon & Florence Puech, 2003. "Evaluating the geographic concentration of industries using distance-based methods," Journal of Economic Geography, Oxford University Press, vol. 3(4), pages 409-428, October.
    4. Gilles Duranton & Henry G. Overman, 2002. "Testing for localisation using micro-geographic data," LSE Research Online Documents on Economics 20071, London School of Economics and Political Science, LSE Library.
    5. Briant, A. & Combes, P.-P. & Lafourcade, M., 2010. "Dots to boxes: Do the size and shape of spatial units jeopardize economic geography estimations?," Journal of Urban Economics, Elsevier, vol. 67(3), pages 287-302, May.
    6. Tomoya Mori & Koji Nishikimi & Tony E. Smith, 2004. "A Divergence Statistic for Industrial Localization," KIER Working Papers 587, Kyoto University, Institute of Economic Research.
    7. Combes, Pierre-Philippe & Overman, Henry G., 2004. "The spatial distribution of economic activities in the European Union," Handbook of Regional and Urban Economics, in: J. V. Henderson & J. F. Thisse (ed.), Handbook of Regional and Urban Economics, edition 1, volume 4, chapter 64, pages 2845-2909 Elsevier.
    8. Ugo Fratesi, 2008. "Issues in the measurement of localization," Environment and Planning A, Pion Ltd, London, vol. 40(3), pages 733-758, March.
    9. Giuseppe Arbia & Giuseppe Espa & Danny Quah, 2007. "A class of spatial econometric methods in the empirical analysis of clusters of firms in the space," Department of Economics Working Papers 0705, Department of Economics, University of Trento, Italia.
    10. Rosenthal, Stuart S. & Strange, William C., 2004. "Evidence on the nature and sources of agglomeration economies," Handbook of Regional and Urban Economics, in: J. V. Henderson & J. F. Thisse (ed.), Handbook of Regional and Urban Economics, edition 1, volume 4, chapter 49, pages 2119-2171 Elsevier.
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    Cited by:
    1. Pablo Jensen & Julien Michel, 2011. "Measuring spatial dispersion: exact results on the variance of random spatial distributions," The Annals of Regional Science, Springer, vol. 47(1), pages 81-110, August.
    2. Arbia, G. & Espa, G. & Giuliani, D. & Mazzitelli, A., 2012. "Clusters of firms in an inhomogeneous space: The high-tech industries in Milan," Economic Modelling, Elsevier, vol. 29(1), pages 3-11.

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